See
Every domain, one schema
Every cost record lands in FOCUS at ingestion, with invoice truth and execution truth joined in one queryable store. No proprietary schema, no translation lag, and roughly 30% lower data-processing cost.
Technology Value Realization 
The Technology Value Realization Platform.
See what your AI, cloud and data spend produces, as well as what it costs.
One engine on the open FOCUS schema covers cloud, AI, data platforms, Kubernetes, on-premise and SaaS, plus any cost domain you add later.
Trusted by Fortune 500 companies and delivered with global systems integrators.
First insight in 48 hours · Fixed annual subscription · EDP and MACC eligible
- SOC 2® Type II
- GDPR compliant
- MCP enabled
Two very different buying journeys.
Pick yours. The platform is the same for both. The first thing you need to see is not.
Enterprise and regulated
Fortune 500, banks, insurers, utilities, public sector
You need the security review answered, a deployment model that keeps data inside your perimeter, and a procurement path that runs through the integrator you already work with.
- BYOC, so DigiUsher is a software provider rather than a data processor
- FCA, PRA, MAS, DORA, FedRAMP and IL2/IL4 mapping
- Delivered by global systems integrators including Infosys, Wipro, Coforge, Persistent Systems and Hitachi Digital
Startups and scale-ups
Series A to D, cloud-native, AI-heavy engineering teams
You need to see it working before you talk to anyone, know it will not tax your growth, and get a unit metric in front of your board by the end of the month.
- First insight within 48 hours of connecting a source
- Flat subscription, never a percentage of your spend
- Cost per merged pull request for AI-heavy engineering
- Marketplace or direct procurement
€1M / 45 days Verified-realized savings at a European enterprise
80% Less time spent on monthly allocation at Exotel, per-product unit economics in its place
25% Cloud cost reduction at DataWeave inside two quarters, with a chargeback model finance signed off
Customers
A leading energy firm 
A leading bank 
A leading bank Delivered and co-sold by
Available on
Azure Marketplace Cloud partner programs
Built on open standards, not proprietary lock-in
- FinOps Foundation alignment Aligned to the Framework, the personas, and the Crawl, Walk, Run maturity model.
- FOCUS-native Every record lands in the FinOps Open Cost and Usage Specification at ingestion.
- Tokenomics AI token cost treated as a first-class discipline, in line with the 2026 Foundation scope.
- MCP enabled Open Model Context Protocol access, through your own assistants and your own RBAC.
The premise
A cost number without a value denominator is an invitation to cut the wrong thing.
- 6 domains
- Cloud, AI, data platforms, Kubernetes, on-premise and SaaS, on one open schema
- 48 hours
- To first insight after connecting a source
- 0%
- Of your spend taken as a fee. Flat annual subscription only
The TVR journey
First-generation FinOps answered the cost question, domain by domain. The question of this cycle is value: what did the spend produce, who owns it, and is it compounding into business outcomes? DigiUsher answers it with one journey, applied uniformly to every technology cost domain.
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01 -
02 Attribute
Every cost to owner and output
Sequenced auditable chargeback: invoice → environment → project → team. Every stage records its rule, inputs and outputs, and attribution quality is graded, so chargeback survives its first audit.
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03 Optimize
Waste out, governed
Domain scenario libraries plus your own rules, each recommendation carrying severity, saving and evidence. In a governed workflow automation the recommendation becomes a pull request, a human approves it, and Terraform applies it. Nothing changes silently.
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04 Realize
Value in business terms
Unit economics per domain: cost per workload, per merged pull request, per pipeline run, per service, composing into AI-inclusive cost per customer. Savings tracked identified → applied → verified-realized.
The composition property
Because every domain lives in one schema, unit metrics compose across domains. Cost per customer can include the Snowflake credits, the Bedrock tokens, the EKS pods and the SaaS seats that serve that customer: one formula, one auditable answer. Point tools each compute their own fraction, and only a platform that holds the whole estate can compute the whole number.
The landscape Established discipline Established discipline The category we built
Technology Value Realization sits between FinOps and TBM, and answers the question neither was built for: what did the spend produce?
Two disciplines already own real ground. FinOps established cloud cost accountability. Technology Business Management established IT financial planning. Both remain necessary, and neither was designed to hold cost and business output in the same schema.
FinOps
Asks: is this cloud cost visible, attributed and optimized?
- Strength: cloud cost accountability, tagging discipline, commitment management
- Scope: public cloud, expanding into AI through the Tokenomics discipline
- Output: showback and chargeback reports, optimization backlogs
- Limit: stops at visibility, with the value denominator out of scope
DigiUsher writes to FOCUS and aligns to the FinOps Foundation. TVR depends on a mature FinOps practice rather than replacing one.
Technology Business Management
Asks: how should IT budget be planned, allocated and defended?
- Strength: IT financial planning, portfolio cost, budget variance
- Scope: the whole IT estate at planning granularity
- Output: budgets, forecasts, application and service cost models
- Limit: planning-layer granularity, neither operational nor real time
DigiUsher feeds TBM. Attributed operational cost and unit economics flow upward into Apptio-class planning models. Enterprises run both.
Technology Value Realization
Asks: what did this cost produce, who owns it, and is the value compounding faster than the spend?
- Strength: cost joined to output in one schema, so the deliverable is value proof
- Scope: cloud, AI, data platforms, Kubernetes, on-premise, SaaS and any future domain
- Output: unit economics per domain, composite cost per customer, savings verified in the bill
- Requires: FinOps maturity beneath it, and complements TBM above it
The operational cost-to-value layer, applied uniformly to every domain.
How the three layers sit together
TBM · planning layer Budgets, portfolio cost, business-unit showback, multi-year plans
TVR · cost-to-value layer One open schema, graded attribution, unit metrics, governed optimization, verified savings
FinOps · practice layer Accountability culture, the FOCUS specification, personas, Crawl, Walk, Run maturity
TVR builds on a FinOps practice rather than replacing it, and it does not produce next year's IT budget. That remains TBM's job.
The shift
For CFO and finance For engineering For FinOps leaders
Move from cost reporting to value realization.
Cost tools stop at visibility. Boards are asking what the spend produced. This is how the two approaches differ.
| Cost-reporting tools Conventional | DigiUsher Technology Value Realization | |
|---|---|---|
| Scope | One domain per tool | Cloud, AI, data platforms, Kubernetes, on-premise and SaaS on one open schema |
| What they show | Yesterday's bill, by service | Live cost by owner, by unit and by business outcome, with attribution quality graded |
| Value metrics | Stops at visibility | Cost per workload, per merged pull request, per pipeline run, per service, and cost per customer with AI included |
| Deployment | SaaS only. Your data leaves you | SaaS, a dedicated instance, or BYOC, with full feature parity and DigiUsher as a software provider rather than a data processor |
| Pricing | Percentage of spend, which penalizes growth | Fixed annual subscription, eligible for EDP drawdown and MACC |
| Action | Dashboards, alerts and spreadsheets | Recommendation to pull request to approval to applied, MCP enabled |
| Automation | Built-in, fixed-scope automation modules | Composes your existing AI and RPA stack into governed workflow automation, with change management built in |
| Savings | Estimated, then forgotten | Tracked from identified, to applied, to verified in the bill. The number finance will sign off |
Cloud, data and AI return in one number, with chargeback finance can defend.
Unit economics per service, and guardrails that fire before the bill arrives.
Auditable sequenced allocation, executive-ready reports, in real time rather than at month end.
Domain editions
Five cost domains, one engine underneath.
Each domain gets its own connectors, waste patterns and signature value metric, on the same open schema, so the metrics compose.
- Cloud AWS · Azure · GCP · OCI Cost per workload
- AI Models · agents · GPU Cost per merged PR
- Data Cloud Databricks · Snowflake · Atlas Cost per pipeline run
- Kubernetes EKS · AKS · GKE · on-prem Cost per service
- On-prem, SaaS & ANY VMware · mainframe · subscriptions Cost per VM · per active seat · per MIPS
All five editions in depth, with connectors, waste scenarios and value metrics →
Connectors
Every source, one schema.
Cloud, data platforms, AI models, coding agents, Kubernetes and SaaS land in FOCUS at ingestion, so a token, a DBU and a cloud instance are directly comparable. A new source is a connector, not a platform release.
Cloud
Data platforms
AI models
Show all 25 connectors Show fewer connectors
Coding agents
Kubernetes
SaaS & on-premise
See how each domain's connectors, waste patterns and value metric work →
Flexible deployment Option 1 Option 2 Option 3 · most chosen by regulated buyers
Three deployment models, one feature set. You choose where the data lives.
Pick the model that fits your regulatory posture. Prompts, responses and tool payloads are discarded at ingestion, whatever the connector configuration, so privacy is built into the pipeline rather than promised in a contract.
SaaS
Hosted by DigiUsher. Fastest time to value.
- First insight within 48 hours
- Shared multi-tenant infrastructure, hosted in EU, US, AUS and ME regions
- SOC 2 Type II and GDPR
Fit
Startups, scale-ups and growth-stage cloud-native teams.
Dedicated instance
Single tenant in a region you pick. Your isolation, our operations.
- Dedicated VPC and dedicated database
- No shared tenancy
- Pinned regions for data residency
Fit
Mid-market enterprise, EU data residency, regulated SaaS.
Bring Your Own Cloud (BYOC)
DigiUsher runs entirely inside your AWS, Azure, GCP, OCI or data center account. No cost, usage, telemetry or workload data leaves your infrastructure.
- Software provider, not a data processor
- Simplifies vendor risk under FCA, PRA, MAS, DORA, FedRAMP and IL2/IL4
- Terraform or Helm deployment through your own CI/CD
Fit
Banking, insurance, public sector.
Your environment
Your cloud account
VPC · cost data · usage logs · billing exports · k8s metrics
DigiUsher
Control plane
Metadata only · dashboards · forecasts · alerts
Under BYOC the whole platform, control plane included, runs inside your perimeter. Individual-level views are RBAC-gated, with an organization-wide aggregate-only mode for works-council and compliance postures. There is an audit record of every connector, credential and visibility change.
The deployment reference: the BYOC perimeter, regulatory mapping and residency answers →
Customer outcomes European enterprise Regulated · cloud · data platforms · SaaS Exotel CPaaS · SaaS DataWeave Retail intelligence · SaaS
What changes when spend becomes provable value.
Constraint
Data residency rules ruled out percentage-of-spend SaaS tools before any evaluation started.
Attribution
System-table-level ingestion put cloud, warehouse and pipeline cost in one ledger, and allocated spend that had been split across three teams.
Unit economics
Cost per pipeline run, tracked from the first week.
Decision
€1M verified in the bill in 45 days, and two pipelines rebuilt rather than cut.
Constraint
Cloud and AI spend climbing faster than revenue, with no per-product unit economics to argue from.
Attribution
Real-time allocation by service, surfaced in the dashboards engineering already used.
Decision
80% less time spent on monthly allocation, and product-level cost owned by the teams that create it. Darshan Datt KS, Director of Engineering
Constraint
Multi-cloud sprawl, no chargeback model, and finance and engineering disagreeing about cost drivers.
Attribution
Allocation engine with shared-service chargeback, and finance-ready reports without a spreadsheet stage.
Decision
25% cloud cost reduction inside two quarters, on a chargeback model finance signed off. Vikranth Ramanola, Co-founder and CTO
Frequently asked questions
The questions buyers ask most.
What is Technology Value Realization (TVR)?
Technology Value Realization (TVR) is the discipline of connecting every technology cost, across AI, cloud, data platforms, Kubernetes, on-premise and SaaS, to the business value it produces. DigiUsher organizes it as seven questions an enterprise has to answer about technology money: whether the platform can run inside your estate, whether the number is right, whose money it is, what the money produced, what it will cost next, where the waste is, and how overspend is prevented.
What cost sources does DigiUsher support?
AWS, Azure, GCP, OCI and Alibaba Cloud billing; Kubernetes at node, pod, cluster, daemonset, replicaset, deployment and namespace level; Databricks, BigQuery and MongoDB Atlas; Anthropic, OpenAI, Cursor, Bedrock, Vertex AI and Azure AI; coding-agent telemetry from Claude Code, Codex and Cursor; on-premise, VMware and mainframe estates; and SaaS subscriptions including GitHub, Microsoft 365, Salesforce, ServiceNow and Google Workspace. Snowflake support is in development. Adding a source means adding a connector, not waiting for a release.
What does it mean that DigiUsher is written to FOCUS?
Every cost record lands in FOCUS, the FinOps Open Cost and Usage Specification, at the moment of ingestion. There is no proprietary intermediate schema and no translation layer. That delivers roughly 30% lower data-processing cost, no translation delay, and a dataset your team owns and can take anywhere. The cost figure is a DigiUsher internal measure, aggregated and anonymized across customer deployments.
How does DigiUsher track AI and LLM costs?
Across three surfaces: managed AI platforms including Bedrock, Vertex AI and Azure AI; direct model providers including Anthropic, OpenAI and Gemini; and engineering agents including Cursor, Claude Code, Copilot, Codex, Windsurf, Gemini CLI and Devin. GPU infrastructure is covered down to MIG-partition level. The AI Attribution Lens joins agent spend to delivered work and reports cost per merged pull request. Prompts and responses are discarded at ingestion by architectural rule.
How is DigiUsher deployed?
Three models with full feature parity: SaaS, a dedicated instance, and Bring Your Own Cloud (BYOC). Under BYOC the platform runs entirely inside your cloud or data center. No cost, usage, telemetry or workload data leaves your infrastructure, and DigiUsher is classified as a software provider rather than a data processor under FCA, PRA, MAS, DORA, FedRAMP and IL2/IL4 regimes.
How is DigiUsher priced?
Flat-rate license pricing based on an annual consumption tier, never a percentage of spend. As technology spend grows, and AI spend can grow tenfold in a year, DigiUsher's price stays flat or increases marginally according to your contractual tier. Procurement runs through our global systems integrators, directly, or via AWS Marketplace drawing down EDP commitments, or Azure Marketplace counting toward MACC.
How fast is time to value?
First insight within 48 hours of connecting a source, measured across our customer base rather than at one account, and full enterprise integration in 2 to 4 weeks. Each stage delivers value on its own, so adoption does not wait on a big-bang program.
Can AI assistants query DigiUsher directly?
Yes. DigiUsher exposes its full data model through the Model Context Protocol (MCP). Claude, Copilot, Gemini or an in-house model can query cost, allocation and value data conversationally, inside your own AI environment, subject to the same role-based access control as every dashboard.
44 more answers, covering TVR, FinOps, AI cost, Kubernetes, allocation and vendor selection →
See what your technology spend is producing.
A 15-minute call about your stack, then first insight within 48 hours of onboarding.
- SOC 2® Type II
- GDPR compliant
- MCP enabled